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20222026
most citedYOLO advances to its genesis: a decadal and comprehensive review of the You Only Look Once (YOLO) series

274 citations · 974 across the 43 of their papers we have counts for

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Showing 2025Show all

21 papers · 1 filter

cs.CV2025

Generalization vs. Specialization: Evaluating Segment Anything Model (SAM3) Zero-Shot Segmentation Against Fine-Tuned YOLO Detectors

Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee +1

Deep learning has advanced two fundamentally different paradigms for instance segmentation: specialized models optimized through task-specific fine-tuning and generalist foundation…

cs.HC2025

PoultryTalk: A Multi-modal Retrieval-Augmented Generation (RAG) System for Intelligent Poultry Management and Decision Support

Kapalik Khanal, Biswash Khatiwada, Stephen Afrifa +4

The Poultry industry plays a vital role in global food security, yet small- and medium-scale farmers frequently lack timely access to expert-level support for disease diagnosis, nu…

cs.CV2025

The SAM2-to-SAM3 Gap in the Segment Anything Model Family: Why Prompt-Based Expertise Fails in Concept-Driven Image Segmentation

Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee

This paper investigates the fundamental discontinuity between the latest two Segment Anything Models: SAM2 and SAM3. We explain why the expertise in prompt-based segmentation of SA…

cs.CV2025★ 8 cited

Ultralytics YOLO Evolution: An Overview of YOLO27, YOLO26, YOLO11, YOLOv8, and YOLOv5 Object Detectors for Computer Vision and Pattern Recognition

Ranjan Sapkota, Manoj Karkee

This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 thro…

cs.CV2025★ 20 cited

Object Detection with Multimodal Large Vision-Language Models: An In-depth Review

Ranjan Sapkota, Manoj Karkee

The fusion of language and vision in large vision-language models (LVLMs) has revolutionized deep learning-based object detection by enhancing adaptability, contextual reasoning, a…

cs.CV2025★ 18 cited

YOLO26: Key Architectural Enhancements and Performance Benchmarking for Real-Time Object Detection

Ranjan Sapkota, Rahul Harsha Cheppally, Ajay Sharda +1

This study presents a comprehensive analysis of Ultralytics YOLO26(also called as YOLOv26), highlighting its key architectural enhancements and performance benchmarking for real-ti…

cs.AI2025★ 1 cited

Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact

Rizwan Qureshi, Ranjan Sapkota, Abbas Shah +16

Can machines truly think, reason and act in domains like humans? This enduring question continues to shape the pursuit of Artificial General Intelligence (AGI). Despite the growing…

cs.CV2025★ 1 cited

3D Reconstruction and Information Fusion between Dormant and Canopy Seasons in Commercial Orchards Using Deep Learning and Fast GICP

Ranjan Sapkota, Zhichao Meng, Martin Churuvija +3

In orchard automation, dense foliage during the canopy season severely occludes tree structures, minimizing visibility to various canopy parts such as trunks and branches, which li…

cs.AI2025

Agentic AI with Orchestrator-Agent Trust: A Modular Visual Classification Framework with Trust-Aware Orchestration and RAG-Based Reasoning

Konstantinos I. Roumeliotis, Ranjan Sapkota, Manoj Karkee +1

Modern Artificial Intelligence (AI) increasingly relies on multi-agent architectures that blend visual and language understanding. Yet, a pressing challenge remains: How can we tru…

cs.RO2025★ 1 cited

UAVs Meet Agentic AI: A Multidomain Survey of Autonomous Aerial Intelligence and Agentic UAVs

Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee

Agentic UAVs represent a new frontier in autonomous aerial intelligence, integrating perception, decision-making, memory, and collaborative planning to operate adaptively in comple…

cs.AI2025★ 4 cited

TRiSM for Agentic AI: A Review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems

Shaina Raza, Ranjan Sapkota, Manoj Karkee +1

Agentic AI systems, built upon large language models (LLMs) and deployed in multi-agent configurations, are redefining intelligence, autonomy, collaboration, and decision-making ac…

cs.SE2025★ 4 cited

Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI

Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee

This review presents a comprehensive analysis of two emerging paradigms in AI-assisted software development: vibe coding and agentic coding. While both leverage large language mode…

cs.AI2025★ 197 cited

AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges

Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee

This review critically distinguishes between AI Agents and Agentic AI, offering a structured, conceptual taxonomy, application mapping, and analysis of opportunities and challenges…

cs.CV2025★ 2 cited

Vision-Language-Action (VLA) Models: Concepts, Progress, Applications and Challenges

Ranjan Sapkota, Yang Cao, Konstantinos I. Roumeliotis +1

Vision-Language-Action (VLA) models mark a transformative advancement in artificial intelligence, aiming to unify perception, natural language understanding, and embodied action wi…

cs.CV2025

Plant Disease Detection through Multimodal Large Language Models and Convolutional Neural Networks

Konstantinos I. Roumeliotis, Ranjan Sapkota, Manoj Karkee +2

Automation in agriculture plays a vital role in addressing challenges related to crop monitoring and disease management, particularly through early detection systems. This study in…

cs.CV2025

A Review of 3D Object Detection with Vision-Language Models

Ranjan Sapkota, Konstantinos I Roumeliotis, Rahul Harsha Cheppally +2

This review provides a systematic analysis of comprehensive survey of 3D object detection with vision-language models(VLMs) , a rapidly advancing area at the intersection of 3D vis…

cs.CV2025★ 7 cited

RF-DETR Object Detection vs YOLOv12 : A Study of Transformer-based and CNN-based Architectures for Single-Class and Multi-Class Greenfruit Detection in Complex Orchard Environments Under Label Ambiguity

Ranjan Sapkota, Rahul Harsha Cheppally, Ajay Sharda +1

This study conducts a detailed comparison of RF-DETR object detection base model and YOLOv12 object detection model configurations for detecting greenfruits in a complex orchard en…

cs.CV2025★ 4 cited

Improved YOLOv12 with LLM-Generated Synthetic Data for Enhanced Apple Detection and Benchmarking Against YOLOv11 and YOLOv10

Ranjan Sapkota, Manoj Karkee

This study evaluated the performance of the YOLOv12 object detection model, and compared against the performances YOLOv11 and YOLOv10 for apple detection in commercial orchards bas…

cs.SE2025★ 5 cited

Comprehensive Analysis of Transparency and Accessibility of ChatGPT, DeepSeek, And other SoTA Large Language Models

Ranjan Sapkota, Shaina Raza, Manoj Karkee

Despite increasing discussions on open-source Artificial Intelligence (AI), existing research lacks a discussion on the transparency and accessibility of state-of-the-art (SoTA) La…

cs.CY2025★ 5 cited

Who is Responsible? The Data, Models, Users or Regulations? A Comprehensive Survey on Responsible Generative AI for a Sustainable Future

Shaina Raza, Rizwan Qureshi, Anam Zahid +14

Generative AI is rapidly moving from research to deployment, elevating the need for responsible development, evaluation, and governance. We conduct a PRISMA guided review of 232 st…

cs.CV2025★ 3 cited

Multimodal Large Language Models for Image, Text, and Speech Data Augmentation: A Survey

Ranjan Sapkota, Shaina Raza, Maged Shoman +2

In the past five years, research has shifted from traditional Machine Learning (ML) and Deep Learning (DL) approaches to leveraging Large Language Models (LLMs) , including multimo…